A deep learning model for snoring detection and vibration notification using a smartwearable gadget
Snoring, a form of sleep-disordered breathing, interferes with sleep quality and quantity, both for the person who snores and often for the person who sleeps with the snorer. Poor sleep caused by snoring can create significant physical, mental, and economic problems. A simple and natural solution for snoring is to sleep on the side, instead of sleeping on the back. In this project, a deep learning model for snoring detection is developed and the model is transferred to an embedded system—referred to as the listener module—to automatically detect snoring. A novel wearable gadget is developed to apply a vibration notification on the upper arm until the snorer sleeps on the side. The gadget is rechargeable, and it is wirelessly connected to the listener module using low energy Bluetooth. A smartphone app—connected to the listener module using home Wi-Fi—is developed to log the snoring events with timestamps, and the data can be transferred to a physician for treating and monitoring diseases such as sleep apnea. The snoring detection deep learning model has an accuracy of 96%. A prototype system consisting of the listener module, the wearable gadget, and a smartphone app has been developed and tested successfully.
Link to Published Version
Khan, T. (2019). A deep learning model for snoring detection and vibration notification using a smart wearable gadget. Electronics, 8(9), 987. https://doi.org/10.3390/electronics8090987